[go: up one dir, main page]

Yi et al., 2018 - Google Patents

A fast and accurate forward vehicle start alarm by tracking moving edges obtained from dashboard camera

Yi et al., 2018

Document ID
5921220969206379326
Author
Yi K
Jung K
Publication year
Publication venue
2018 15th IEEE International Conference on Advanced Video and Signal Based Surveillance (AVSS)

External Links

Snippet

The Forward Vehicle Start Alarm (FVSA) is a technique for determining whether or not a forward vehicle begins to start when the traffic signal changes from STOP to GO. And it is expected to be one of the important functions of Advanced Driver Assistance System …
Continue reading at ieeexplore.ieee.org (other versions)

Classifications

    • G—PHYSICS
    • G06—COMPUTING; CALCULATING; COUNTING
    • G06K—RECOGNITION OF DATA; PRESENTATION OF DATA; RECORD CARRIERS; HANDLING RECORD CARRIERS
    • G06K9/00—Methods or arrangements for reading or recognising printed or written characters or for recognising patterns, e.g. fingerprints
    • G06K9/00624—Recognising scenes, i.e. recognition of a whole field of perception; recognising scene-specific objects
    • G06K9/00791—Recognising scenes perceived from the perspective of a land vehicle, e.g. recognising lanes, obstacles or traffic signs on road scenes
    • G06K9/00798—Recognition of lanes or road borders, e.g. of lane markings, or recognition of driver's driving pattern in relation to lanes perceived from the vehicle; Analysis of car trajectory relative to detected road
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING; COUNTING
    • G06K—RECOGNITION OF DATA; PRESENTATION OF DATA; RECORD CARRIERS; HANDLING RECORD CARRIERS
    • G06K9/00—Methods or arrangements for reading or recognising printed or written characters or for recognising patterns, e.g. fingerprints
    • G06K9/00624—Recognising scenes, i.e. recognition of a whole field of perception; recognising scene-specific objects
    • G06K9/00791—Recognising scenes perceived from the perspective of a land vehicle, e.g. recognising lanes, obstacles or traffic signs on road scenes
    • G06K9/00805—Detecting potential obstacles
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING; COUNTING
    • G06K—RECOGNITION OF DATA; PRESENTATION OF DATA; RECORD CARRIERS; HANDLING RECORD CARRIERS
    • G06K9/00—Methods or arrangements for reading or recognising printed or written characters or for recognising patterns, e.g. fingerprints
    • G06K9/20—Image acquisition
    • G06K9/32—Aligning or centering of the image pick-up or image-field
    • G06K9/3233—Determination of region of interest
    • G06K9/3241—Recognising objects as potential recognition candidates based on visual cues, e.g. shape
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING; COUNTING
    • G06K—RECOGNITION OF DATA; PRESENTATION OF DATA; RECORD CARRIERS; HANDLING RECORD CARRIERS
    • G06K9/00—Methods or arrangements for reading or recognising printed or written characters or for recognising patterns, e.g. fingerprints
    • G06K9/00624—Recognising scenes, i.e. recognition of a whole field of perception; recognising scene-specific objects
    • G06K9/00791—Recognising scenes perceived from the perspective of a land vehicle, e.g. recognising lanes, obstacles or traffic signs on road scenes
    • G06K9/00825—Recognition of vehicle or traffic lights
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING; COUNTING
    • G06K—RECOGNITION OF DATA; PRESENTATION OF DATA; RECORD CARRIERS; HANDLING RECORD CARRIERS
    • G06K9/00—Methods or arrangements for reading or recognising printed or written characters or for recognising patterns, e.g. fingerprints
    • G06K9/00624—Recognising scenes, i.e. recognition of a whole field of perception; recognising scene-specific objects
    • G06K9/00791—Recognising scenes perceived from the perspective of a land vehicle, e.g. recognising lanes, obstacles or traffic signs on road scenes
    • G06K9/00818—Recognising traffic signs
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING; COUNTING
    • G06K—RECOGNITION OF DATA; PRESENTATION OF DATA; RECORD CARRIERS; HANDLING RECORD CARRIERS
    • G06K9/00—Methods or arrangements for reading or recognising printed or written characters or for recognising patterns, e.g. fingerprints
    • G06K9/36—Image preprocessing, i.e. processing the image information without deciding about the identity of the image
    • G06K9/46—Extraction of features or characteristics of the image
    • G—PHYSICS
    • G08—SIGNALLING
    • G08G—TRAFFIC CONTROL SYSTEMS
    • G08G1/00—Traffic control systems for road vehicles
    • G08G1/01—Detecting movement of traffic to be counted or controlled
    • G08G1/04—Detecting movement of traffic to be counted or controlled using optical or ultrasonic detectors
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING; COUNTING
    • G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
    • G06T2207/00—Indexing scheme for image analysis or image enhancement
    • G06T2207/30—Subject of image; Context of image processing
    • G06T2207/30248—Vehicle exterior or interior
    • G06T2207/30252—Vehicle exterior; Vicinity of vehicle
    • G—PHYSICS
    • G08—SIGNALLING
    • G08G—TRAFFIC CONTROL SYSTEMS
    • G08G1/00—Traffic control systems for road vehicles
    • G08G1/16—Anti-collision systems
    • G08G1/167—Driving aids for lane monitoring, lane changing, e.g. blind spot detection
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING; COUNTING
    • G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
    • G06T2207/00—Indexing scheme for image analysis or image enhancement
    • G06T2207/10—Image acquisition modality
    • G06T2207/10016—Video; Image sequence
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING; COUNTING
    • G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
    • G06T7/00—Image analysis
    • G06T7/20—Analysis of motion
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING; COUNTING
    • G06K—RECOGNITION OF DATA; PRESENTATION OF DATA; RECORD CARRIERS; HANDLING RECORD CARRIERS
    • G06K2209/00—Indexing scheme relating to methods or arrangements for reading or recognising printed or written characters or for recognising patterns, e.g. fingerprints
    • G06K2209/23—Detecting or categorising vehicles

Similar Documents

Publication Publication Date Title
Rezaei et al. Robust vehicle detection and distance estimation under challenging lighting conditions
US9836657B2 (en) System and method for periodic lane marker identification and tracking
US7566851B2 (en) Headlight, taillight and streetlight detection
US9251708B2 (en) Forward collision warning trap and pedestrian advanced warning system
Wang et al. Driver assistance system for lane detection and vehicle recognition with night vision
US10380434B2 (en) Vehicle detection system and method
US8848980B2 (en) Front vehicle detecting method and front vehicle detecting apparatus
Wu et al. A Real‐Time Embedded Blind Spot Safety Assistance System
CN111753593A (en) Real-time detection method, system and device for riding vehicle of vehicle-mounted all-round system
Saboune et al. A visual blindspot monitoring system for safe lane changes
Suryakala et al. Vision based vehicle/pedestrian detection in traffic surveillance system
Munajat et al. Vehicle detection and tracking based on corner and lines adjacent detection features
Wu et al. Overtaking Vehicle Detection Techniques based on Optical Flow and Convolutional Neural Network.
Kanhere et al. Real-time detection and tracking of vehicle base fronts for measuring traffic counts and speeds on highways
Guzman et al. Car detection methodology in outdoor environment based on histogram of oriented gradient (HOG) and support vector machine (SVM)
Dai et al. A driving assistance system with vision based vehicle detection techniques
Huang et al. Nighttime vehicle detection and tracking base on spatiotemporal analysis using RCCC sensor
Chen et al. Robust rear light status recognition using symmetrical surfs
Kuo et al. Vision-based vehicle detection in the nighttime
Yi et al. A fast and accurate forward vehicle start alarm by tracking moving edges obtained from dashboard camera
Tourani et al. Challenges of video-based vehicle detection and tracking in intelligent transportation systems
Vijverberg et al. High-level traffic-violation detection for embedded traffic analysis
Kumar Vehicle detection in monocular night-time grey-level videos
Tsuchiya et al. Real-time vehicle detection using a single rear camera for a blind spot warning system
Phoon et al. Real-time forward collision alert system using raspberry Pi